Video

Brief Oral Papers

Session: Oral Presentation Session 02: Neurocognitive Disorders, Delirium, Neuropsychiatry and Catatonia

Mapping The Relationship Between White Matter Lesions and Depression in Patients with Multiple Sclerosis

Friday, November 11, 2022

11:00 AM – 12:30 PM

Location: Room 206-207

Presenting Author(s)

Erica Baller, MD, MS

Assistant Professor of Psychiatry
Department of Psychiatry, University of Pennsylvania
Philadelphia, Pennsylvania

Co-Author(s)

MC

Matthew Cieslak, PhD

Director of Neuroinformatics
University of Pennsylvania
philadelphia, Pennsylvania
SC

Sydney Covitz

Neuroinformatics Software Engineer
University of Pennsylvania
philadelphia, Pennsylvania
MM

Melissa Martin, MS

Graduate Student
University of Pennsylvania
philadelphia, Pennsylvania
MS

Matthew Schindler, MD, PhD

Assistant Professor of Neurology
University of Pennsylvania
philadelphia, Pennsylvania
Ameena Elahi, MPA, RT(R), CIIP

Senior CIM Technical Analyst
University of Pennsylvania
philadelphia, Pennsylvania
AM

Abigail Manning

Clinical Research Coordinator
University of Pennsylvania
philadelphia, Pennsylvania
CM

Clyde Markowitz, MD

Associate Professor of Neurology, Director of Penn Multiple Sclerosis Center
University of Pennsylvania
philadelphia, Pennsylvania
CP

Christopher Perrone, MD

Assistant Professor of Clinical Neurology
University of Pennsylvania
philadelphia, Pennsylvania
SS

Shan Siddiqi, MD

Instructor
Brigham and Women's Hospital, Harvard Medical School
Boston, Massachusetts
RS

Russell Shinohara, PhD

Associate Professor of Biostatistics in Biostatistics and Epidemiology
University of Pennsylvania
Philadelphia, Pennsylvania
TS

Theodore Satterthwaite, MD

Associate Professor, Director of PENNLinc(Penn Lifespan Informatics and Neuroimaging Center)
University of Pennsylvania
philadelphia, Pennsylvania

Abstract: Background/Significance:

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the United States, with up to 50% of patients experiencing a lifetime depression (Feinstein, 2014). However, mechanisms of depression in MS remain under-investigated. Previous research using lesion network mapping has demonstrated that strokes in gray matter associated with depression disrupt a reproducible depression network (Siddiqui, 2021). However, such methods have not been used to investigate how white matter lesions (WMLs) relate to depression in MS.

Methods:

Participants with MS were identified from the electronic medical record. The depressed individuals (DI) included persons with evidence of depression as indicated by a ICD-10 depression diagnosis(F32-F34.*), a prescription for antidepressant medication, or screening positive via PHQ2/9(n=232, age(SD)=49(12), %females=86). The age- and sex-matched non-depressed comparators (NDC) included persons with no prior depression diagnosis, psychiatric medications, and were asymptomatic on PHQ2/9 (n=148, age(SD)=47(13); %females=79). Structural MRI was obtained as part of routine care at 3T using a research-quality protocol. WMLs were automatically segmented using the algorithm Method for Inter-Modal Segmentation Analysis and projected onto a standard template (Valcarcel, 2018). Eighty-seven white matter tracts(WMT) were evaluated. The volume of WMTs intersecting each lesion was computed via streamline filtering in DSI Studio. Age and diagnostic effects were assessed with general linear models and T-tests. Enrichment of effects in a previously described depression network was also evaluated (Siddiqi, 2021). The IRB at the University of Pennsylvania approved this study.

Results:

Streamline filtering recapitulated previously known patterns of MS disease, with high proportions of streamlines impacted in the optic radiations, inferior fronto-occipital fasciculi, medial longitudinal fasciculi, and corticopontine tracts. Greater age was associated with higher disease burden in 54/87 WMTs (P_FDR< 0.05). The burden of MS lesions was higher within versus outside the depression network (P< 2.2 x10^-16). DIs had a higher mean disease burden across all WMTs (P< 0.05).

Discussion:

We present a novel approach for calculating the relationship of WML to disease burden. We show that DIs have greater overall lesion burden as compared NDCs and demonstrate that MS lesions preferentially impact areas within the depression network, suggesting a potential mechanism for the high prevalence of depression in patients with MS.

Conclusions/implications:

We provide new evidence supporting a relationship between WML and depression in MS.

References:

Feinstein, A., Magalhaes, S., Richard, J.-F., et al., 2014. The link between multiple sclerosis and depression. Nature Reviews Neurology 10, 507–517. https://doi.org/10.1038/nrneurol.2014.139

Siddiqi, S.H., Schaper, F.L.W.V.J., Horn, et al., 2021. Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease. Nat Hum Behav 5, 1707–1716. https://doi.org/10.1038/s41562-021-01161-1

Valcarcel, A.M., Linn, K.A., Vandekar, S.N., et al., 2018. MIMoSA: An Automated Method for Inter-Modal Segmentation Analysis of Multiple Sclerosis Brain Lesions. J Neuroimaging 28, 389–398. https://doi.org/10.1111/jon.12506